Characterization of nanoparticles
In this study, nanomaterials (MnO2 nanoparticles, M-NPs; Fe2O3 nanoparticles, F-NPs; and MnFe2O4 nanoparticles, MF-NPs) and conventional ionic materials (FeCl2 and MnCl2) were derived from ordinary commercial production. Nanomaterials were characterized accordingly. Scanning electron microscopy (SEM) (Fig. 1a) and transmission electron microscopy (TEM) (Additional file 1: Fig. S1) results indicated that nanomaterials used in this study were irregular granules. Line scanning results indicated that the content of manganese and oxygen in M-NPs was 40.12% and 59.88%, respectively (Fig. 1b), that the content of iron and oxygen in F-NPs was 52.14% and 47.86%, respectively, and that the content of iron, manganese, and oxygen in MF-NPs was 29.64%, 10.84%, and 59.52% (Additional file 1: Table S1). The zeta potential value (Fig. 1c) of M-NPs, F-NPs, and MF-NPs in deionized water (pH = 6.5) was − 6.8 ± 0.3 mV, − 9.2 ± 0.3 mV, and − 1.5 ± 0.2 mV, respectively, and the average particle size distribution was 223.43 nm for MF-NPs, 59.34 nm for F-NPs, and 108.71 for M-NPs (Fig. 1d). Fourier transform infrared (FTIR) spectroscopy showed no specific surface functional groups in MF-NPs (Additional file 1: Fig. S2). The photoelectron spectrum of MF-NPs showed that Fe 2p3/2 peaks for FeO, Fe3O4, and Fe2O3 appeared at binding energies of 709.9 eV, 710.7 eV, and 711.8 eV, respectively [33, 34], coupled with the satellite peaks at binding energies of 713.4 eV and 718.8 eV in the Fe 2p region (Fig. 1e). The Mn 2p3/2 peaks for MnO, Mn3O4, and Mn2O3 appeared at binding energies of 641.2 eV, 642.2 eV, and 643.2 eV, respectively, coupled with satellite peaks at a binding energy of 644.4 eV [33, 35].
Synergistic ROS generation of MF-NPs
The mechanism by which MF-NPs catalyzed ROS production was studied by comparing the Mn-based nano-oxides, Fe-based nano-oxides, and ionic compounds (Fig. 2a). The determination results of the increase value in dissolved oxygen and the number of O2 bubbles showed that under M-NPs, M-NPs+F-NPs, and FeCl2 exposures, O2 generation capability was increased within 30 min, which was faster than under MF-NP exposure (Fig. 2b and Additional file 1: Fig. S3). A time-dependent H2O2 assay at pH 6.5 indicated that nano-sized M-NPs and M-NPs+F-NPs decomposed almost all H2O2 within 1 h, and FeCl2 also achieved similar effects within 5 h (Fig. 2c). Under MF-NP exposure, about 10% H2O2 residue was still detected 1 week later. Only a weak H2O2 decomposition was observed under F-NP and FeCl2 exposures. After adding H2O2 to reaction system (pH 6.5), ∙OH concentration in the presence of NPs was evaluated by detecting the fading degree of methylene blue (MB) induced by ∙OH (Fig. 2d). The ∙OH yield under MF-NP exposure was significantly higher than that under other exposures except FeCl2, for FeCl2, Fe2+ which could be rapidly converted to Fe3+, but could not be sustainable. Similar results were observed in the spectral curve of the time dynamic response (Additional file 1: Fig. S4). The results showed that M-NPs, F-NPs+M-NPs, and FeCl2 could convert intermediate ∙OH to generate more O2, whereas MF-NPs only a few convert. Compared with FeCl2, MF-NPs had a lasting hydroxyl radical production efficiency in FTR system containing Fe2+ and Mn2+.
Response to MF-NPs exposure and Fenton reaction
To evaluate the response of soybean growth to different nanomaterials, soybeans were planted in substrates containing different nanomaterials and their physiological and nitrogen fixation indexes were analyzed at different inoculation time points. The plant height analysis indicated a general decrease in the height of the soybean plants treated with a certain concentration of manganese-based materials (M-NPs+F-NPs, M-NPs, MF-NPs, MnCl2), especially that treated with MF-NPs. However, almost no obvious change in plant height was observed for the treatment with F-NPs and FeCl2 at all concentrations (Additional file 1: Figs. S5, S6). The stem diameter (Additional file 1: Fig. S7) analysis showed a completely opposite trend to that of plant height, with a larger diameter in the groups treated with M-NPs+F-NPs, M-NPs, MF-NPs, and MnCl2 than in the groups treated with F-NPs and FeCl2, and the most significant stem diameter difference was observed in the MF-NP treatment group at all concentrations, which might be due to dwarfing induced by ROS. Root length analysis indicated that root growth was obviously promoted by all the treatments except F-NP treatment at certain concentrations, which might be due to the advantages of iron and manganese as massive element in plant physiological growth (Additional file 1: Figs. S8, S9). Biomass analysis (Additional file 1: Fig. S10) showed only a significant increase in MF-NP and MnCl2 treatment groups, which was consistent with the increasing trend of nodule number (Additional file 1: Fig. S11) and weight (Additional file 1: Fig. S12), suggesting that biomass increase might be related to the increase in nitrogen nutrition. Under the treatment with different concentrations of MF-NPs, the plant exhibited a height decrease of 15.04%, 13.99%, and 18.10% in response to 10 mg L−1, 50 mg L−1, and 100 mg L−1 MF-NPs, respectively (Fig. 3a); a stem diameter increase of 10.4% at 1 mg L−1, 11.88% at 10 mg L−1, 8.05% at 50 mg L−1, and 10.06% at 100 mg L−1) (Fig. 3b); a biomass increase at 0.1 mg L−1, 1 mg L−1, and 10 mg L−1, with a maximum increase of 25.70% (1.05 g) at 10 mg L−1 (Fig. 3c); a maximum nodule weight increase of 0.28 g at 1 mg L−1 (Fig. 3e) and a maximum nodule number increase of 71 at 10 mg L−1 with various degrees of increase at 1 mg L−1, 10 mg L−1, and 50 mg L−1 (Fig. 3d). The growth phenotype investigation showed that the root length exhibited a significant increase of 25.36%, 26.19%, and 20.92% at 1 mg L−1, 10 mg L−1 and 50 mg L−1, respectively, and that plant growth promotion effect was weakened at a high concentration of 50 or 100 mg L−1(Fig. 3f, g).
The response of soybean growth and nitrogen fixation indicators to Fenton reaction was examined at the optimal promoting concentration (10 mg L−1) under two different acidity matrixes (pH 6.5) and (pH 5.2) conditions. As shown in Fig. 3m, in the case of low pH-induced ROS redundancy, no significant difference was observed in plant height (Fig. 3h). Under 0.01% and 0.1% H2O2 exposure, the stem diameter at pH 6.5 matrix was respectively 6.62% and 8.71% higher than that at pH 5.2, and under 0.01% and 0.1% H2O2 exposure at pH 6.5, the stem diameter was 10.05% and 11.89% higher than that without H2O2 exposure at the same pH value (Fig. 3i). Biomass exhibited an increase of 15.06% under 0.01% H2O2 exposure at pH 6.5 matrix relative to pH 5.2 (Fig. 3j). Meanwhile, the nodule number (Fig. 3k) and weight (Fig. 3l) under 0.01%, 0.1%, and 0.3% H2O2 exposure at pH 6.5 were 1.35, 1.78, 1.43 (number) and 1.40, 1.25, and 1.47 (weight) times as much as those at pH 5.2, respectively. The weight under 0.01% H2O2 exposure at pH 6.5 was 15.32% higher than that without H2O2 exposure at pH 6.5. Root length (Fig. 3m, n) showed significant difference between pH 5.2 and pH 6.5 at low H2O2 concentrations (0.01% and 0.1%) and tended to be stable with the increase of H2O2 concentration, but excessively high H2O2 concentration (> 0.1%) induced the suppression of the root length (independent of pH) and all growth indicators (regardless strong or weak acid).
Seedling roots response to MF-NP exposure
The effect of MF-NP exposure on the ROS level in soybean roots was examined by tissue staining and localization of soybean root tips and root maturation zone. The roots were stained with either 3, 3-diaminobenzidine (DAB) or nitroblue tetrazolium (NBT) to observe H2O2 and O2∙− production, respectively. Compared with the control, MF-NP-treated plants showed the accumulation of H2O2 and O2∙− in the root tips (Fig. 4b, c) and root maturation zone (Fig. 4d, e). The degree of coloring was calculated with ImageJ software [31]. The content of H2O2 and O2∙− in the MF-NPs treatment group was 6.52 and 2.08 times as high as that in the control group in the root tip, and 2.73 and 2.99 times in the root maturation zone. The detection results of total ROS content in root tips and root maturation zone were consistent with those described above (Additional file 1: Fig. S13).
Evaluation of nodulation and nitrogen fixation efficiency
Nodulation starts from the flavonoid-induced Rhizobium infection, leading to the expression of nodulation factor (Nod-F). In nodulation process, ROS first induces root hair curling, and then the development of infection lines and nodule primordia [36]. In this study, we counted the early curled root hairs. As shown in Fig. 4f and g, MF-NPs exposure increased the curling of root hairs in the maturation zone, which was 3.38 times of that in the control group, thus providing a prerequisite for the development and growth of mature nodules. With the further growth of nodules, early immature nodules visible to the naked eye were formed, and their number at different stages was used to locate the nodule development period. The difference in the distribution of immature nodules was observed between the control group and MF-NP treatment group during the 20-day growth period (Fig. 5a). The number of immature nodules in the 20-day growth period was found to be 7.43 times of that in the control group, indicating that the exposure to 10 mg L−1 MF-NPs could prolong the early development of the nodules, leading to a continuous increase in the number of nodules (Fig. 5b).
Root phenotype and nodule development were used to evaluate the influence of MF-NP treatment on the growth and development of underground parts (Fig. 6a). Analysis of root morphology showed no obvious suppression effect of MF-NPs on root, and further analysis of the nodule section showed no obvious difference in the cell morphology and size between the infected area and the non-infected area, and the development of the transport tissue was normal. Fluorescence staining with SYTO9 and PI showed that the infected rhizobia in the cells of the nodule exhibited viability, and that the number of total infected rhizobia (green) and the dead rhizobia (red) in MF-NPs treatment group was comparable to that in the control group (Fig. 6b). These observations indicated that MF-NPs exposure had no obvious effect on the growth and development of soybean roots and nodules, and it could even increase root length.
The acetylene reduction method (ARM) was used to evaluate the nitrogenase activity in the mature nodules. All the treatments resulted in no significant difference in the nitrogenase activity per unit mass nodule, implying that the exposure to these nanomaterials would neither promote nitrogenase activity nor impose stress on the nitrogen fixation function of nodules (Fig. 6c). Furthermore, the total nitrogen fixation within 2 h in a single soybean plant (Fig. 6d) was evaluated by analyzing the reduction activity of the whole plant nodules. The 2.51-, 2.37-, 1.99-time increase in total nitrogen fixation under MF-NPs treatment (10 mg L−1, 50 mg L−1, and 100 mg L−1) and 1.79-time increase under MnCl2 (27.27 mg L−1) treatment, relative to the control group.
Gene expression analysis
The mechanism by which MF-NPs exposure induced nodulation was investigated by transcriptome sequencing analysis of root samples from control and treatment groups at different stage (early stage, day 4; middle stage, day 8; and late stage, day 12 post inoculation). First, principal component analysis (PCA) was performed to determine the impacts of MF-NPs on soybean (Fig. 7a). A total of 595 DEGs were detected in the early stage with 100 up-regulated and 495 down-regulated, and 2676 DEGs in the late stage with 912 up-regulated and 1764 down-regulated. Hierarchical clustering analysis showed significant differences in different stages (Additional file 1: Figs. S14a, c and S15). However, only 38 DEGs (35 up-regulated and 3 down-regulated) were detected in the middle stage, indicating that MF-NPs exposure in the middle stage made little difference in the transcription level (Additional file 1: Fig. S15b). The Venn diagram showed the relatively few overlapping DEGs in three different stages (Fig. 7b).
The relationship between DEGs and nodulation metabolism was further explored by KEGG, NR, SwissProt, TrEMBL, KOG, GO and Pfam as a reference. The 5, 0, and 36 DEGs in the early, middle and late stages were found to be nodulation-related (Nod-R) with 2, 0, and 31 up-regulated, respectively (Fig. 7c). The late-stage DEGs were shown in Additional file 1: Table S2. The promotion effect of MF-NPs exposure on nodulation was mainly found in the early and late stages, especially in the late stage. We further analyzed flavonoid-related (Fla-R) DEGs (Fig. 7d, Additional file 1: Table S3) and ROS-related (ROS-R) DEGs (Fig. 7e, Additional file 1: Table S4) at late stage. Of 61 ROS-R DEGs, 51 down-regulated and 10 up-regulated. In total, 47 differential Fla-R DEGs were detected, of which 41 down-regulated and 6 up-regulated. In order to study the expression patterns of DEGs under different processing conditions, the FPKM of the DEGs was normalized, followed by K-means cluster analysis (Fig. 7f). Based on the expression patterns, Nod-R DEGs were clustered in class 12, and no significant difference between treatment group and control group in the early and middle stages, but a significant increase in the expression level of Nod-R DEGs was observed under MF-NPs exposure in the late stage. After optimization and clustering, the ROS-R DEGs were clustered into class 4, class 5, class 7, class 10, and class 11, all of which showed an opposite trend to class 12, which might be due to the feedback regulation triggered by the MF-NP-induced ROS increase. The Fla-R DEGs were mainly clustered into Class 4, Class 5, and Class 11, which was overlapped with the clustering of ROS-R, suggesting a synergistic relationship between these two types of DEGs. Our results were consistent with previous reports that expression of flavonoids could induce ROS expression [37, 38]. In addition, our results indicated that the expression patterns of Fla-R DEGs were completely opposite to those of Nod-R DEGs. Class 2 and class 3 showed the trend similar to that of Class12, indicating these 3 classes of DEGs might have synergistic effect, which remains to be further investigated.
GO enrichment analysis classified DEGs into biological process, cellular component and molecular function according to gene functions. Different genes in organisms exert biological functions through interactions. The 50 most significantly enriched GO-Terms were selected and classified according to GO database annotations. In the early stage (Additional file 1: Fig. S16), DEGs were mainly enriched in the pathways related to photosynthetic system inhibition and ROS metabolism. In the middle stage, DEGs were mainly enriched in the pathways (Additional file 1: Fig. S17) involved in cation transport. In the late stage (Fig. 8a), DEGs were mainly enriched in the pathways related to the secondary metabolism. Flavonoids (yellow box) serve as the initial inducers of legume nodulation. Our results indicated that the expression level of Fla-R genes was significantly reduced in the late stage, which might be due to the feedback regulation induced by the ROS increase in the early and middle stages. This was consistent with the expression of ROS-R genes in root samples (Fig. 8a). The microorganism-plant symbiosis system related to nodulation was significantly enhanced (as shown in Fig. 8a red box and Additional file 1: Fig. S18), which was specifically manifested as the enhancement in nodulation, nitrogen fixation, endocytic vesicle membrane, bacteroid-containing symbiosome, peribacteroid membrane, and other functions. The obtained GO terms were subjected to topGO directed acyclic graph (DAG) analysis. During symbiont process, the microorganism-plant interspecies interactions occurred nodulation upstream (red box in Fig. 8b and Additional file 1: Fig. S18). Changes in the metabolism of ROS were also reflected in multiple hierarchical pathways (Fig. 8b and Additional file 1: Fig. S19). The KEGG pathway analysis revealed the top 20 most significantly enriched pathways (Fig. 8c) with “biosynthesis of secondary metabolites” pathway exhibited the highest enrichment degree, which might be due to peroxide stress induction in soybean roots (Fig. 8c, Additional file 1: Fig. S20). KEGG pathway analysis indicated that “Flavonoid synthesis” pathway was significantly enriched, which was consistent with the results of GO enrichment analysis (Fig. 8c, Additional file 1: Fig. S21). KEGG pathway analysis also showed that glutathione metabolism pathway was significantly enriched, which might be due to the continuous increase in ROS, and this pathway enrichment contributed to the metabolic balance between root tissues and relieve oxidative stres (Fig. 8c and Additional file 1: Fig. S22). In addition, the enrichment of nitrogen metabolism pathway was observed, which might be explained by the increase in nitrogen fixation in some mature nodules in the late stage (Fig. 8c and Additional file 1: Fig. S23).
MF-NPs-mediated AON response
According to previous studies, the relevant autoregulation of nodulation (AON) pathway genes were identified [15, 17]. To evaluate the regulatory effect of MF-NPs exposure on the AON pathway, we analyzed the expression levels of the related genes, including NFR1/NFR5 (nodulation factor), GmNINa (nodulation gene), ENOD40s (nodulation response gene), NNC1 (nodule number control), miR172c (fine-tuning rhizobium infection and nodule organogenesis), GmRIC1 and GmRIC2 (specific CLAVATA/ESR-related (CLE) peptides in soybean responsible for producing root-derived nodulation), and GmNARK (nodule autoregulation receptor kinase) (Fig. 9). In the nodulation pathway, our study showed that the expression levels of Fla-R and ROS-R genes in MF-NPs exposure groups were overall down-regulated, while Nod-R genes showed a up-regulation expression trend. The expression of nodulation factors (NFR1/5) was low and not significantly different between MF-NPs exposure group and CK, which might be cause of the down-regulation of the ROS-R genes. In addition, GmNINa, miR172c, and ENOD40s all showed an up-regulation trend with significantly increasing ROS levels during this process. Therefore, the up-regulated expression of nodulation genes (GmNINa, miR172c, and ENOD40s) and the low expression of nodulation factors (NFR1/5) might be due to the increase in exogenous ROS. In the AON pathway, NARK made no obvious response to significant up-regulation of GmRIC2 and GmRIC1expressions, which might be attributed to the inhibition of CLE peptides responsible for long-distance transportation. Therefore, MF-NPs exposure could enhance the expression of nodulation genes, meanwhile inhibiting the AON pathway, thereby achieving an increase in the number of nodules.